Identification of type VI secretion system effector-immunity pairs using structural bioinformatics

The type VI secretion system (T6SS) is an important mediator of microbe–microbe and microbe–host interactions. Gram-negative bacteria use the T6SS to inject T6SS effectors (T6Es), which are usually proteins with toxic activity, into neighboring cells. Antibacterial effectors have cognate immunity proteins that neutralize self-intoxication. Here, we applied novel structural bioinformatic tools to perform systematic discovery and functional annotation of T6Es and their cognate immunity proteins from a dataset of 17,920 T6SS-encoding bacterial genomes. Using structural clustering, we identified 517 putative T6E families, outperforming sequence-based clustering. We developed a logistic regression model to reliably quantify protein–protein interaction of new T6E-immunity pairs, yielding candidate immunity proteins for 231 out of the 517 T6E families. We used sensitive structure-based annotation which yielded functional annotations for 51% of the T6E families, again outperforming sequence-based annotation. Next, we validated four novel T6E-immunity pairs using basic experiments in E. coli. In particular, we showed that the Pfam domain DUF3289 is a homolog of Colicin M and that DUF943 acts as its cognate immunity protein. Furthermore, we discovered a novel T6E that is a structural homolog of SleB, a lytic transglycosylase, and identified a specific glutamate that acts as its putative catalytic residue. Overall, this study applies novel structural bioinformatic tools to T6E-immunity pair discovery, and provides an extensive database of annotated T6E-immunity pairs.

, Figure EV2" etc... in the text and their respective legends should be included in the main text after the legends of regular figures.
-For the figures that you do NOT wish to display as Expanded View figures, they should be bundled together with their legends in a single PDF file called *Appendix*, which should start with a short Table of Content.Appendix figures should be referred to in the main text as: "Appendix Figure S1, Appendix Figure S2" etc. -Additional Tables/Datasets should be labeled and referred to as Table EV1, Dataset EV1, etc. Legends have to be provided in a separate tab in case of .xlsfiles.Alternatively, the legend can be supplied as a separate text file (README) and zipped together with the Table/Dataset file.See detailed instructions here: https://www.embopress.org/page/journal/17574684/authorguide#expandedview11) For more information: There is space at the end of each article to list relevant web links for further consultation by our readers.Could you identify some relevant ones and provide such information as well?Some examples are patient associations, relevant databases, OMIM/proteins/genes links, author's websites, etc... 12) Author contributions: CRediT has replaced the traditional author contributions section because it offers a systematic machine readable author contributions format that allows for more effective research assessment.Please remove the Authors Contributions from the manuscript and use the free text boxes beneath each contributing author's name in our system to add specific details on the author's contribution.More information is available in our guide to authors.13) Disclosure statement and competing interests: We updated our journal's competing interests policy in January 2022 and request authors to consider both actual and perceived competing interests.Please review the policy https://www.embopress.org/competing-interests and update your competing interests if necessary.
14) Every published paper now includes a 'Synopsis' to further enhance discoverability.Synopses are displayed on the journal webpage and are freely accessible to all readers.They include a short stand first (maximum of 300 characters, including space) as well as 2-5 one-sentences bullet points that summarizes the paper.Please write the bullet points to summarize the key NEW findings.They should be designed to be complementary to the abstract -i.e.not repeat the same text.We encourage inclusion of key acronyms and quantitative information (maximum of 30 words / bullet point).Please use the passive voice.Please attach these in a separate file or send them by email, we will incorporate them accordingly.
Please also suggest a striking image or visual abstract to illustrate your article as a PNG file 550 px wide x 300-600 px high.Share synopsis text and image, as well as eTOC: Please note that these would be the final versions and changes during proofing are usually not allowed 15) As part of the EMBO Publications transparent editorial process initiative (see our policy here: https://www.embopress.org/transparent-process#Review_Process),Molecular Systems Biology will publish online a Peer Review File (PRF) to accompany accepted manuscripts.In the event of acceptance, this file will be published in conjunction with your paper and will include the anonymous referee reports, your point-by-point response and all pertinent correspondence relating to the manuscript.Let us know whether you agree with the publication of the PRF and as here, if you want to remove or not any figures from it prior to publication.Please note that the Authors checklist will be published at the end of the PRF.
Molecular Systems Biology has a "scooping protection" policy, whereby similar findings that are published by others during review or revision are not a criterion for rejection.Should you decide to submit a revised version, I do ask that you get in touch after three months if you have not completed it, to update us on the status.I look forward to receiving your revised manuscript.
I have some minor comments:

General comments
The authors have used evolved structural components such as Hcp, PAAR, PAAR-like and VgrG for the identification of the putative effectors.I agree that this approach is appropriate, but I am curious to know why they have not used other classical T6SS markers like MIX, FIX, RIX or even adaptors like EagR or Tap for this search, or the classical structural non-evolved components.All of them would have been useful to increase the reach of the study.
I would like to kindly suggest the improvement of the manuscript's English language.Although the overall content is wellstructured and clear, some sentences appear to be grammatically complex or could benefit from smoother transitions.
The content of the Discussion section has many redundancies from the Results section.A more distinct separation between the two sections, with the Discussion focussing on the interpretation and implications of the results rather than restating them, would improve the readability of the manuscript.
The authors emphasise that the manuscript serves as a valuable resource for the scientific community by offering predictions for 265 T6E domain families.However, the presentation and explanation of the supplementary data make it challenging for users to effectively use this information.The manuscript should include a more detailed and accessible explanation of the supplementary data to ensure clarity and ease of use for the scientific community, increasing the impact of this work.

Specific comments
Line 50-it is not only sometimes that they are called "cargo" effectors, it is how the field has defined them.Line 55 -the word "effector" is repeated.Line 62. Immunity proteins also protect from sister cells firing and not only self-intoxication.Line 67.Type VI effector-immunity pairs can be denoted as EI pair.Line 71.Authors could consider including here an Opinion article discussing this subject (PMID: 33687778 DOI: 10.1111/1462-2920.15457)Line 141.The authors could consider specifying that DUIF4150 is a PAAR-like domain.Figure 2 D. The Y-axis is lacking a clear title indicating the represented parameter (survival of E. coli BL21).Line 262-264 The authors suggest that because the T6IC1 putative immunity gene is predicted to encode a transmembrane anchoring domain, the activity of T6EC1 could be in the periplasm.This is not necessarily true, especially if it does not have a signal to be transported to this compartment.I understand that the results confirm their hypothesis, but since they do not discuss the effect of the effector being expressed in the cytosol, this data is not conclusive.The target could be the side of the inner membrane that is facing the cytosol.The Integrated Microbial Genomes and Microbiomes should be named IMG/M as indicated on their website and not IMG.Lines 341-342 are repetitive to lines 342-344.Line 403, the reference to Figure 4D is missing.
Reviewer #2: The manuscript "Identification of type VI secretion system effector-immunity pairs using structural bioinformatics" from Geller et al. is interesting and pleasant to read.The work presents an interesting approach to predict protein-protein interactions in bacteria based on AlphaFold2 and FoldSeek, which are newborn technologies in the structural bioinformatics field.In particular, here the authors focus on the proteins belonging to the T6SS, an important bacterial machinery able to inject effectors into preys.The manuscript describes an in silico approach to detect bacterial proteins secreted by the T6SS and the associated immunity proteins that protect the bacteria from these proteins.The method allows functional annotation of effectors and detection of the immunity partner, and finally the database is shared with the community.Some selected predictions are experimentally validated.The authors focus on 'specialized' effectors, which are fused with components of the T6SS.Using sequence analysis, they extensively identify the specialized effectors in bacterial genomes.Structures of extra-domain were predicted with Alphafold2 and the structural comparison with Foldseek was carried out to suggest functional annotations.Immunity proteins were predicted based on their genomic location (downstream and in the vicinity of effectors) and the AlphaFold prediction of the effector/immunity protein dimer.Experimental validation was carried out on four pairs of effector + immunity proteins.
The main ideas and hypotheses are clearly stated.The results support the claim.The findings will be of interest for the community of microbiologists.Here I list comments to improve the methods.
A possible validation of the classifier that they developed is to see how it behaves against noise.Thus I wonder what happens if you take all your known effector-immunity pairs and randomize them (ie, you randomize the pairing between the effector and immunity protein), and see what is the resulting iPTM score for the randomized pairs, and how they are classified.I guess iPTM should be low, but it is worth seeing to have additional trust on the classifier.Furthermore, it would be nice to see the same analysis for a set of predicted effector-immunity pairs, ie, randomize the pairs as described above.
The structural comparison with FoldSeek is used to propose a functional annotation of the specialized effector extra domains.At the level of structural similarity, one can expect that a given structure can match with several proteins of different functions.It would be interesting to know how this multiplicity is handled.
The authors performed a mutation on a candidate effector, and state that "we performed a point mutagenesis of the catalytic glutamate to glutamine, causing minimal changes in steric structures".Although it seems safe to postulate that the mutation will not perturb the structure, I would suggest the authors to be less affirmative.
Minor points line 79 I think it is generally accepted to say that AF2 didn't solve the protein folding problem, but improved protein structure prediction, only for folded domains.Protein folding is a more complex problem involving the dynamics and the pathway of the process, which is still not systematically resolved.line 97 thier -> their The above evaluation is about the in silico approach, and does not concern the experimental validation.

Reviewer #3:
In this manuscript, the authors present a large scale integrated bioinformatic predictive structural analysis of effector and immunity genes of the type VI secretion system of the phylum Pseudomonodota.This pipeline leverages validated effector and immunity gene pairs to discover new pairs.Further, the authors validate the toxicity of 4 new previously unexplored effectors and demonstrate the neutralization capacity of the associated immunity genes.All together, the paper is well written and interesting, the method is powerful and provides more comprehensive insight into the spectrum of T6SS genes.Generally, I like the paper and I only have a few comments, which I list below.
My major comment is that I request that the authors significantly tone down the strength of language of their interpretations throughout the entire manuscript.The alphafold modeling, while powerful, is prediction only and should not be overinterpreted.For example, the RMSD values of the T6E1-4 effectors is somewhat poor.While these values reflect structural similarity across the whole proteins, he authors do not specifically compare in this structural analysis potential enzymatic active sites (e.g.colicin M https://doi.org/10.1074/jbc.M109.093583)and, lacking this comparison and followup experimental mutational analysis of potential active sites in T6E1-4, I think the authors need to make abundantly clear that effector mechanism is unknown and therefore speculation about mechanism should be clearly conveyed as it is -speculation.
The authors search for "core" proteins (Paar, vgrg, hcp, etc) but not for structural T6SS proteins.It seems possible that many genomes lack functional T6SS and I would think that assessing if the entire repertoire of T6SS structural proteins is found encoded in the genomes examined would be very important.Just as an example, in Lines 504-513, the authors discuss effectors that lack immunity, which is counter to expectations.In these genomes, are structural genes missing?Another possibility, unless I misunderstand the analysis described on lines 239-243 in which I think only looked for immunity downstream of the effector, is that the immunity gene is actually upstream of the effector The pie chart figure in 3B is unreadable.I recommend grouping/collapsing some of the categories into "other".
There is no information on biological replicates performed for the toxicity experiments and no description of statistical tests used -the authors must add this information.Likewise, there is no quantitative information regarding data from microscopy experiments.There are many useful tools (e.g.microbeJ) that facilitate quantitative cell biological examination of microscopy datasets and I urge the authors to add this, otherwise the examples shown lack value.
There is a tendency to cite recent reviews instead of primary literature and I encourage the authors to cite both.For example, the statement on line 62 regarding the role of immunity should include reference Hood et al PMID 20114026.
The authors should provide analysis code in a publicly accessible repository e.g.github.

Reviewer #1:
This manuscript describes a timely work that uses novel and powerful predicted tools (A.I.) that allow the advance of the T6SS field.Specifically, the authors applied structural bioinformatic tools to identify and annotate 517 putative T6SS effector families from a dataset of 17,920 bacterial genomes.Through structural clustering and a logistic regression model, they also identified candidate immunity proteins for 231 T6E families and validated four novel EI pairs through experiments in E. coli.The novelty of the work resides in the use of structural clustering instead of sequence-based clustering, increasing the number of putative EI families identified; and structure-based annotation increasing the quality of the functional annotations.
Thanks for your close reading of the paper and the detailed review.I am glad to hear you think it is timely and that you appreciate the novelty in using structure-based clustering.
I have some minor comments:

General comments
The authors have used evolved structural components such as Hcp, PAAR, PAAR-like and VgrG for the identification of the putative effectors.I agree that this approach is appropriate, but I am curious to know why they have not used other classical T6SS markers like MIX, FIX, RIX or even adaptors like EagR or Tap for this search, or the classical structural non-evolved components.All of them would have been useful to increase the reach of the study.
Since I wanted to focus and highlight the bioinformatic aspect, especially on the application of novel in silico tools, I wanted to make sure that I was 100% certain that the multitude of proteins under analysis were bona fide T6SS effectors.To ensure this, I used T6SS structural N-termini only.It is a great suggestion to apply the same methodology to any classical T6SS markers appearing at the N-terminal, as well as chaperones/accessories of the T6SS.Future research can now reliably use our pipeline and apply it as you suggest, which could lead to a more comprehensive database.I added a sentence about this in the Discussion section: "The methodology in this study can be expanded to other N-terminal T6SS markers like MIX, FIX, and RIX domains, amongst others."I would like to kindly suggest the improvement of the manuscript's English language.Although the overall content is well-structured and clear, some sentences appear to be grammatically complex or could benefit from smoother transitions.
Okay thanks for the suggestion.I did notice in my fresh reading of the text that there were many run-on and complex sentences.I have gone through the manuscript and tried to simplify and complex sentences by splitting them up, and tried to add transitions where necessary.
For example, I cut a giant run on sentence to two sentences: "T6E-immunity pairs are actively researched because the T6SS is important to microbial ecology via their key role in niche colonization and pathogen-host interaction.Furthermore, T6Es can also be developed as 4th Mar 2024 1st Authors' Response to Reviewers potential new antimicrobials, for medical and agricultural applications."I found more examples of long sentences and did the same.Furthermore, I changed the tenses of the sentences to make them more active and less wordy.
I hope now you kind it more readable, yet without any loss of understanding.
The content of the Discussion section has many redundancies from the Results section.A more distinct separation between the two sections, with the Discussion focussing on the interpretation and implications of the results rather than restating them, would improve the readability of the manuscript.
I changed the discussion to be more focused on the interpretation of the results rather than with restating the findings.I also removed Discussion topics from the Results section.
For example, I removed "Another benefit of in silico quantification of the binding affinity of putative T6E-immunity pairs is that it can aid in deciding which pairs to study further in the laboratory" from the results section, along with similar statements, which truly belong in the discussion section.
I also shortened the Discussion section's first paragraph, which was a long 20 lines that detailed and restated the findings of the paper to about half size (12 lines), which is as minimal as I could get it.This should keep the focus on interpretation and further implications.
The authors emphasise that the manuscript serves as a valuable resource for the scientific community by offering predictions for 265 T6E domain families.However, the presentation and explanation of the supplementary data make it challenging for users to effectively use this information.The manuscript should include a more detailed and accessible explanation of the supplementary data to ensure clarity and ease of use for the scientific community, increasing the impact of this work.This is really useful feedback because I do think the structural clusters could help a lot of researchers trying to formulate a mechanism of action of an unannotated effector protein, so it's of paramount importance that it is understandable.I added a tab to the supplementary table with a detailed explanation of the clusters with a color-coded example going from individual gene accession IDs to structural clusters.Furthermore, I added a second tab explaining the "Immunity Protein" and "Annotation" tabs in more detail.I hope this helps to make it clearer.

Specific comments
Line 50-it is not only sometimes that they are called "cargo" effectors, it is how the field has defined them.Fixed.
Line 62. Immunity proteins also protect from sister cells firing and not only self-intoxication.I added this information on line 62 (and on line 511).Line 67.Type VI effector-immunity pairs can be denoted as EI pair.I appreciate the suggestion, and it is true that I use "T6E-immunity pairs" many times in this manuscript, rather than the more typical "E-I pair" or "EI pair" nomenclature.The reason why I chose the former is because I also speak about the putative effectors alone many times.I felt that then the logical shorthand for the effectors would simply be "E", and that does not sound good to me.So since it is a minor suggestion, I respectfully will keep our current nomenclature.
Line 141.The authors could consider specifying that DUIF4150 is a PAAR-like domain.Added this information in line 141.Line 262-264 The authors suggest that because the T6IC1 putative immunity gene is predicted to encode a transmembrane anchoring domain, the activity of T6EC1 could be in the periplasm.This is not necessarily true, especially if it does not have a signal to be transported to this compartment.I understand that the results confirm their hypothesis, but since they do not discuss the effect of the effector being expressed in the cytosol, this data is not conclusive.The target could be the side of the inner membrane that is facing the cytosol.This is a great point, and based on what is written, you are right that multiple models of possible subcellular localization can be formulated.I accidentally forgot to include more details about the transmembrane helix in the text that explain why I chose the periplasmic hypothesis.I forgot to write that the transmembrane helix is actually predicted to be largely facing outside (to the periplasm), so I updated the text to reflect this: "Because the T6IC1 putative immunity gene was predicted to encode a transmembrane anchoring domain with the bulk of the protein facing the periplasm, we hypothesized that the activity of T6EC1 is in the periplasm (Supplementary Figure 3A) ".Furthermore, in Supplementary Figure 3A, I added the details in the legend: "The transmembrane prediction is as follows: residues 1-6 are inside, residues 7-26 are transmembrane helices, and residues 27-157 are outside (i.e. in the periplasm)."I'm glad your close reading of the paper caught this.
(Interestingly, as a side note, the canonical colicin M does not seem to have activity when overproduced in the cytoplasm [PMC8469651], so the simplest expectation would be that it is the same for T6EC1.While canonical colicin M is taken in by a membrane bound receptor, T6SS effectors have the ability to penetrate membranes, so perhaps T6EC1 has different constraints and potential cytosolic activity… an interesting topic for a future study) The Integrated Microbial Genomes and Microbiomes should be named IMG/M as indicated on their website and not IMG.Fixed.
Lines 341-342 are repetitive to lines 342-344.The extra sentence was removed.
Line 403, the reference to Figure 4D is missing.Fixed.
Reviewer #2: The manuscript "Identification of type VI secretion system effector-immunity pairs using structural bioinformatics" from Geller et al. is interesting and pleasant to read.The work presents an interesting approach to predict protein-protein interactions in bacteria based on AlphaFold2 and FoldSeek, which are newborn technologies in the structural bioinformatics field.In particular, here the authors focus on the proteins belonging to the T6SS, an important bacterial machinery able to inject effectors into preys.The manuscript describes an in silico approach to detect bacterial proteins secreted by the T6SS and the associated immunity proteins that protect the bacteria from these proteins.The method allows functional annotation of effectors and detection of the immunity partner, and finally the database is shared with the community.Some selected predictions are experimentally validated.The authors focus on 'specialized' effectors, which are fused with components of the T6SS.Using sequence analysis, they extensively identify the specialized effectors in bacterial genomes.Structures of extradomain were predicted with Alphafold2 and the structural comparison with Foldseek was carried out to suggest functional annotations.Immunity proteins were predicted based on their genomic location (downstream and in the vicinity of effectors) and the AlphaFold prediction of the effector/immunity protein dimer.Experimental validation was carried out on four pairs of effector + immunity proteins.
The main ideas and hypotheses are clearly stated.The results support the claim.The findings will be of interest for the community of microbiologists.Here I list comments to improve the methods.
Thanks for reading the manuscript, and I am glad to hear you think it will be interesting for the broader community.
A possible validation of the classifier that they developed is to see how it behaves against noise.Thus I wonder what happens if you take all your known effector-immunity pairs and randomize them (ie, you randomize the pairing between the effector and immunity protein), and see what is the resulting iPTM score for the randomized pairs, and how they are classified.I guess iPTM should be low, but it is worth seeing to have additional trust on the classifier.Furthermore, it would be nice to see the same analysis for a set of predicted effector-immunity pairs, ie, randomize the pairs as described above.
I love the logic here and because of that, this is precisely what I thought would be the best training data for the classifier.To be sure I don't feed garbage data into my classifier, I trained it using known T6E-immunity pairs from the SecReT6 database, and I specifically chose those that have experimental validation.For a negative set, I indeed did as you suggest, I randomized the T6E-immunity pairs so they are not supposed to bind one another.Indeed, the ipTM scores were low, as you surmised, and led to good stats for the training of a model seen in Supplementary Figure 2A.In Figure 2B, you can see that the same analysis for the predicted pairs, i.e. those with no experimental validation, and that the classifier does an excellent job separating the randomized pairs from the cognate pairs.An interesting question about this classifier is whether perhaps it is applicable to all kinds of effector-immunity pairs from different secretion systems, and even to toxin-antitoxin pairs, which could be a nice topic for further study.In the future study, I would indeed use your same idea of randomization to test how well the ipTM score works to predict binding, too.
The structural comparison with FoldSeek is used to propose a functional annotation of the specialized effector extra domains.At the level of structural similarity, one can expect that a given structure can match with several proteins of different functions.It would be interesting to know how this multiplicity is handled.
I manually curated the top structural homolog "hits" from the structure-structure search process, and I saw that in many cases, it was clear that the protein had one very specific function.For example, the colicin M homolog discussed in the manuscript was a clear one-to-one hit with one possible annotation.However, as you suggest, there was also detection of homology between one query protein with multiple proteins with various annotations.This was usually because of homology of a domain in putative T6E with a small domain such as LysM, which is quite a widespread generalist domain and has unclear implications for T6E function.This LysM domain can therefore be a domain in many multi domain proteins, and these may have different annotations due to variance in the other domains.Since the E-values, RMSD, as well as the manual curations showed the homolog was trustworthy, I still wanted to list something as its annotation.I tried my best to be descriptive and as to not accidentally mislead members of the community, so for example, I would have just written the domain that it matches, LysM, rather than guessing which overall protein annotation is correct from the multiplicity of annotations.In the future, structural data will be more organized, clustered, and hierarchical, making it easier to give proper annotations in an organized fashion (indeed work like this has begun https://www.nature.com/articles/s41586-023-06510-w).Also automated annotation with the help of deep learning will be able to systematize tasks like this that I did here manually, and this will also help with consistency.Future studies may use tools like ProteInfer (https://elifesciences.org/articles/80942) or later versions of them.I am optimistic about the future of these kinds of structure-structure comparison that will only get better as we collect more data and use novel tools to organize and analyze them.
The authors performed a mutation on a candidate effector, and state that "we performed a point mutagenesis of the catalytic glutamate to glutamine, causing minimal changes in steric structures".Although it seems safe to postulate that the mutation will not perturb the structure, I would suggest the authors to be less affirmative.
I understand that this sentence was a bit overstated, as I was genuinely excited at how simply changing an oxygen to a nitrogen could phenotypically have such a dramatic effect!But I do agree we don't really know in any detail about steric effects, so I changed it to "To test this, we performed a point mutagenesis of the catalytic glutamate to glutamine (E108Q), which makes a minimal change to the side-chain structure, yet changes its chemical nature".
Minor points line 79 I think it is generally accepted to say that AF2 didn't solve the protein folding problem, but improved protein structure prediction, only for folded domains.Protein folding is a more complex problem involving the dynamics and the pathway of the process, which is still not systematically resolved.
Good point.As you say, the protein folding problem has many parts: "The 'protein folding problem' consists of three closely related puzzles: (a) What is the folding code?(b) What is the folding mechanism?(c) Can we predict the native structure of a protein from its amino acid sequence?"(PMID 18573083).There are definitely a lot of nuances here that I did not get into since it is outside of the scope of the paper.I changed the text to reflect a breakthrough in "protein structure prediction" rather than to the protein folding problem as a whole.line 97 thier -> their Fixed.
The above evaluation is about the in silico approach, and does not concern the experimental validation.

Reviewer #3:
In this manuscript, the authors present a large scale integrated bioinformatic predictive structural analysis of effector and immunity genes of the type VI secretion system of the phylum Pseudomonodota.This pipeline leverages validated effector and immunity gene pairs to discover new pairs.Further, the authors validate the toxicity of 4 new previously unexplored effectors and demonstrate the neutralization capacity of the associated immunity genes.All together, the paper is well written and interesting, the method is powerful and provides more comprehensive insight into the spectrum of T6SS genes.Generally, I like the paper and I only have a few comments, which I list below.
Thanks for your review, and it is good to hear you thought it was interesting and that the method was powerful!My major comment is that I request that the authors significantly tone down the strength of language of their interpretations throughout the entire manuscript.The alphafold modeling, while powerful, is prediction only and should not be overinterpreted.For example, the RMSD values of the T6E1-4 effectors is somewhat poor.While these values reflect structural similarity across the whole proteins, he authors do not specifically compare in this structural analysis potential enzymatic active sites (e.g.colicin M https://doi.org/10.1074/jbc.M109.093583)and, lacking this comparison and followup experimental mutational analysis of potential active sites in T6E1-4, I think the authors need to make abundantly clear that effector mechanism is unknown and therefore speculation about mechanism should be clearly conveyed as it is -speculation.I agree that this manuscript is not meant to make any definitive interpretations, especially regarding the mechanism of actions of the putative effectors.I tried to be careful to emphasize that this paper was mainly about the use of the tools and how they are a significant improvement upon sequence-based methods.For example, in the discussion of the submitted manuscript, I wrote, "We emphasize that the main focus of this study was to explore the use of novel tools to see how they could augment T6E discovery and functional characterization.Future work beyond the scope of this manuscript will explore each of these T6E structural clusters for a higher-resolution understanding of their activities and of their mechanisms of action."I understand your concerns, and in order that there is no doubt to the reader, I added more statements to this section of the manuscript to make it crystal clear.The updated statement is: "We emphasize that the main focus of this study was to explore the use of novel tools to see how they could augment T6E discovery and functional characterization.We were careful to note that Foldseek-based annotation is useful for generating accurate hypotheses of mechanisms of action.We sought to perform simple experiments to show that empirical data supports, rather than falsifies, our hypotheses.The experiments presented in this study are indeed in line with the hypotheses generated with the help of Foldseek, but are not meant to be exhaustive.Future work beyond the scope of this manuscript will explore each of these T6E structural clusters for a higher-resolution understanding of their activities and of the specific molecular determinants of their mechanisms of action." Beyond the discussion, I made many edits in the paper, for example I added: "Further experiments are needed to confirm the details of the mechanism of action and that the putative effector is indeed secreted in a T6SS-dependent manner."Another example of a similar statement that I added: "Although further in vitro experiments on purified protein must be performed to ultimately confirm the mechanism of action, this result is in line with the hypothesis that T6EC4 is an endonuclease" amongst other edits.
As you rightly mentioned, the next experimental step would be to look at conserved residues that perhaps represent potential active sites for mutational analysis, which you can see in Figure 2C.The yellow residues are conserved, and interestingly seem to all be occluded by the putative immunity protein (according to the alphafold-multimer model).In the case of T6EC3, which I thought was the most interesting of the effectors, I did take the next step of doing an experimental mutational analysis of a potential active site.I was happy to see that it seems that T6EC3's homologous putative catalytic residue is necessary for toxic activity (Figure 4D).In a future experimental study, I agree the next steps would be to explore more mutations of putative catalytic active site residues, and to do in vitro assays if possible to understand the targeting.It would be good to do this for the other effectors, which I think can be the focus of future work(s).
The authors search for "core" proteins (Paar, vgrg, hcp, etc) but not for structural T6SS proteins.It seems possible that many genomes lack functional T6SS and I would think that assessing if the entire repertoire of T6SS structural proteins is found encoded in the genomes examined would be very important.Just as an example, in Lines 504-513, the authors discuss effectors that lack immunity, which is counter to expectations.In these genomes, are structural genes missing?Another possibility, unless I misunderstand the analysis described on lines 239-243 in which I think only looked for immunity downstream of the effector, is that the immunity gene is actually upstream of the effector I was also concerned, as you are, that looking only at "core" proteins may not be specific enough for the analysis, so I only analyzed genomes encoding for T6SS overall.I defined all the genomes in the analysis as T6SS-encoding genomes if they have at least eight T6SS structural domains, which are listed in a Supplementary Table 2 (for example, pfam12790 representing TssJ, IPR010263 representing TssK, etc.).Therefore, I believe that the genomes can safely be defined as encoding for full T6SS operons, at least for this specific analysis.
In the discussion, I mention a few biological reasons we may not be finding immunity proteins for each effector, chiefly among them is that the effectors are anti-eukaryotic.Further reasons include generalized immunity mechanisms like cell wall modification, immunity islands, and stress responses (Hersch et al, 2020a and2020b;Le et al, 2020;Ross et al, 2019).In terms of the parameters used in the analysis, I was extra conservative by following the model that immunity proteins are likely small proteins (<700 amino acids in length based on the SecReT6 database of immunity proteins), that are likely encoded downstream in the same "sense" on the DNA.Of course you are completely right that the immunity protein can be encoded upstream, but because the main goal of the analysis was to show that alphafold-multimer could be used to quantify the interaction between a putative effector and its cognate immunity protein, I did not want to risk adding any upstream gene that does not follow the canonical model of effector immunity genomic organization.Now that we see the utility of alphafold-mulitmer, we and others in the community can indeed expand this analysis by looking upstream as well for immunity proteins if needed using the logistic regression model we developed.
The pie chart figure in 3B is unreadable.I recommend grouping/collapsing some of the categories into "other".
Okay, I did exactly as you suggested and added an "other" category for the unreadable parts.
There is no information on biological replicates performed for the toxicity experiments and no description of statistical tests used -the authors must add this information.Likewise, there is no quantitative information regarding data from microscopy experiments.There are many useful tools (e.g.microbeJ) that facilitate quantitative cell biological examination of microscopy datasets and I urge the authors to add this, otherwise the examples shown lack value.
I apologize for the oversight, I added the biological replicate information and a non-parametric statistical test as appropriate for the drop assay quantification in the figure legend (Figure 2D).I updated the materials and methods as well.
The microscopy does indeed have a quantification for rounding, in Supplementary Figure 4, using a program we developed based on the foundation model Cellpose (Stringer et al, 2021) that we called cellstats (https://github.com/noamblum/cellstats).We also performed the appropriate non-parametric test for differences in aspect ratio and found rounding was caused by the expression of the T6E.Unfortunately the DNA puncta was more difficult to quantify, but with further development of this tool, it may be possible.I can say that the microscopy images are representative of what we have seen overall, and some will be submitted to the journal for archiving of source data.
There is a tendency to cite recent reviews instead of primary literature and I encourage the authors to cite both.For example, the statement on line 62 regarding the role of immunity should include reference Hood et al PMID 20114026.
There is definitely a spectrum between using primary literature and using reviews, and I agree with your assessment that I tend to naturally use reviews.I went through and added more primary sources-including the one you suggest here-and I hope this re-balances my tendencies.Thank you for the submission of your revised manuscript to Molecular Systems Biology.We have now received the enclosed reports from the referees that were asked to re-assess it.As you will see the reviewers are now globally supportive and I am pleased to inform you that we will be able to accept your manuscript pending the following final amendments: 1) In the main manuscript file, please do the following: -Please include up to 5 keywords -Please format the Data availability section according to the example below: The computer code produced in this study is available in the following database: -Modeling computer scripts: GitHub (https://github.com/SysBioChalmers/GECKO/releases/tag/v1.0)-Please rename "Conflict of Interest Statement" to "Disclosure and competing interests statement".We updated our journal's competing interests policy in January 2022 and request authors to consider both actual and perceived competing interests.Please review the policy https://www.embopress.org/competing-interests and update your competing interests if necessary.
2) In the Materials and Methods, please take care of the following: -Please ensure that a statement on whether or not blinding was done is included in the Materials and Methods even if no blinding was done.Please also be sure to update the Author Checklist, indicating that this has been included in the manuscript.-Please rename the movie to Movie EV1 and update its callout in the main manuscript text.The legend should be removed from the main manuscript and should be included as a separate file zipped together with the movie.5) Tables: Please rename Tables EV1-EV2 to Dataset EV1-EV2.Each dataset will need its legend removed from the manuscript and added to the corresponding file in a separate tab.Please update their callouts in main manuscript text.6) Synopsis: -Synopsis image: Please upload the image separately (not in the manuscript) as a high-resolution jpeg file 550 pixels wide x (250-400) pixels high.Currently the image file is too large.
-Synopsis text: Please provide a short standfirst (maximum of 300 characters, including space), limit the bullet points to max. 5 and upload it as a separate .docfile.Please write the bullet points to summarise the key NEW findings.They should be designed to be complementary to the abstract -i.e.not repeat the same text.We encourage inclusion of key acronyms and quantitative information (maximum of 30 words / bullet point).Please use the passive voice.
-Please check your synopsis text and image before submission with your revised manuscript.Please be aware that in the proof stage minor corrections only are allowed (e.g., typos).7) Source Data: Please ensure that your source data are uploaded as a single source data file (zipped) per figure, with the panels clearly visible in the folder structure.e.g.all the Source data files for figure 4 need to be saved in a single folder and this needs to be zipped and then uploaded as "SD figure 4.zip" file.8) Please update the README file available on Github or provide a new file with practical use instructions for potential future users of your code.9) As part of the EMBO Publications transparent editorial process initiative (see our policy here: https://www.embopress.org/transparent-process#Review_Process),Molecular Systems Biology will publish online a Peer Review File (PRF) to accompany accepted manuscripts.This file will be published in conjunction with your paper and will include the anonymous referee reports, your point-by-point response and all pertinent correspondence relating to the manuscript.Let us know whether you agree with the publication of the PRF and as here, if you want to remove or not any figures from it prior to publication.Please note that the Authors checklist will be published at the end of the PRF.10) Please provide a point-by-point letter INCLUDING my comments as well as the reviewer's reports and your detailed responses (as Word file).---------------------------------------------------------------------------Please click on the link below to submit the revision online: https://msb.msubmit.net/cgi-bin/main.plex----------------------------------------------------------------------------Reviewer #1: The authors have done an excellent job reviewing the manuscript.I am happy with their responses to the concerns and suggestions raised during the review process.I have no further comments to add but to congratulate the authors for a great work.A minor thing: Line 540 -please use "Hcp" instead of "HCP" Reviewer #2: The reviewers responded to all my questions.
Reviewer #3: I thank the authors for responding to my initial review in detail and I am largely satisfied with their edits and additions.I recommend using terminology such as "neutralize" or "prevent toxicity" instead of "save", which occurs periodically throughout the manuscript.
19th Mar 2024 Manuscript Number: MSB-2024-12200R Title: Identification of type VI secretion system effector-immunity pairs using structural bioinformatics Dear Dr Levy, Thank you for the submission of your revised manuscript to Molecular Systems Biology.We have now received the enclosed reports from the referees that were asked to re-assess it.As you will see the reviewers are now globally supportive and I am pleased to inform you that we will be able to accept your manuscript pending the following final amendments: We are glad to hear this good news! 1) In the main manuscript file, please do the following: -Please include up to 5 keywords I added 5 keywords below the abstract, separated by slashes, as per the instructions for authors.
-Please format the Data availability section according to the example below: The computer code produced in this study is available in the following database: -Modeling computer scripts: GitHub (https://github.com/SysBioChalmers/GECKO/releases/tag/v1.0)I re-formatted this section using the phrasing that you provided here.
-Please rename "Conflict of Interest Statement" to "Disclosure and competing interests statement".We updated our journal's competing interests policy in January 2022 and request authors to consider both actual and perceived competing interests.Please review the policy https://www.embopress.org/competing-interests and update your competing interests if necessary.I updated the statement as requested.
2) In the Materials and Methods, please take care of the following: -Please ensure that a statement on whether or not blinding was done is included in the Materials and Methods even if no blinding was done.Please also be sure to update the Author Checklist, indicating that this has been included in the manuscript.I included a statement on blinding ("Blinding was not employed as it was deemed not relevant to the experimental design and objective") and I updated the Author Checklist accordingly.-Please note that we require exact p-values to be reported.Currently exact p-values are not provided in Figure EV 4a or its legend.In the previous draft, I reported the p-value previously as equal to zero, as the number was so small, the computer's floating point minimum was reached.In order to comply with your request, I used logarithms to calculate the order of magnitude of the p-value, which is 1E-1871.I wrote this p-value into Figure EV 4a.
-Please rename the movie to Movie EV1 and update its callout in the main manuscript text.The legend should be removed from the main manuscript and should be included as a separate file zipped together with the movie.Okay, I changed the name and removed the legend from the main manuscript.5) Tables: Please rename Tables EV1-EV2 to Dataset EV1-EV2.Each dataset will need its legend removed from the manuscript and added to the corresponding file in a separate tab.Please update their callouts in main manuscript text.Done.

6) Synopsis:
-Synopsis image: Please upload the image separately (not in the manuscript) as a highresolution jpeg file 550 pixels wide x (250-400) pixels high.Currently the image file is too large.Okay I uploaded it separately in the size and format requested.
-Synopsis text: Please provide a short standfirst (maximum of 300 characters, including space), limit the bullet points to max. 5 and upload it as a separate .docfile.Please write the bullet points to summarise the key NEW findings.They should be designed to be complementary to the abstract -i.e.not repeat the same text.We encourage inclusion of key acronyms and quantitative information (maximum of 30 words / bullet point).Please use the passive voice.
-Please check your synopsis text and image before submission with your revised manuscript.Please be aware that in the proof stage minor corrections only are allowed (e.g., typos).I wrote the standfirst and have it in a separate file.7) Source Data: Please ensure that your source data are uploaded as a single source data file (zipped) per figure, with the panels clearly visible in the folder structure.e.g.all the Source data files for figure 4 need to be saved in a single folder and this needs to be zipped and then uploaded as "SD figure 4.zip" file.Okay, I put related figure source data together into zipped format.8) Please update the README file available on Github or provide a new file with practical use instructions for potential future users of your code.
I added a section to the README section, describing the inputs and outputs of the relevant scripts and their dependencies.This should make the pipeline accessible to future users.9) As part of the EMBO Publications transparent editorial process initiative (see our policy here: https://www.embopress.org/transparent-process#Review_Process),Molecular Systems Biology will publish online a Peer Review File (PRF) to accompany accepted manuscripts.This file will be published in conjunction with your paper and will include the anonymous referee reports, your point-by-point response and all pertinent correspondence relating to the manuscript.Let us know whether you agree with the publication of the PRF and as here, if you want to remove or not any figures from it prior to publication.Please note that the Authors checklist will be published at the end of the PRF.---------------------------------------------------------------------------Reviewer #1: The authors have done an excellent job reviewing the manuscript.I am happy with their responses to the concerns and suggestions raised during the review process.I have no further comments to add but to congratulate the authors for a great work.I am glad we satisfied your concerns and suggestions, and I appreciate the congratulations!Thanks for the detailed review!A minor thing: Line 540 -please use "Hcp" instead of "HCP" Good catch -Changed.

Reviewer #2:
The reviewers responded to all my questions.Great, thank you for your helpful review!Reviewer #3: I thank the authors for responding to my initial review in detail and I am largely satisfied with their edits and additions.I recommend using terminology such as "neutralize" or "prevent toxicity" instead of "save", which occurs periodically throughout the manuscript.
Glad to hear you're largely satisfied with the edits and additions, thanks for your careful review!I changed the term "saved" in figure 2 legend, as well as in the main text.
9th Apr 2024 2nd Revision -Editorial Decision 9th Apr 2024 Manuscript number: MSB-2024-12200RR Title: Identification of type VI secretion system effector-immunity pairs using structural bioinformatics Dear Dr Levy, Thank you again for sending us your revised manuscript.We are now satisfied with the modifications made and I am pleased to inform you that your paper has been accepted for publication.Your manuscript will be processed for publication by EMBO Press.It will be copy edited and you will receive page proofs prior to publication.Please note that you will be contacted by Springer Nature Author Services to complete licensing and payment information.
You may qualify for financial assistance for your publication charges -either via a Springer Nature fully open access agreement or an EMBO initiative.Check your eligibility: https://www.embopress.org/page/journal/17444292/authorguide#chargesguideShould you be planning a Press Release on your article, please get in contact with embo_production@springernature.com as early as possible in order to coordinate publication and release dates.
If you have any questions, please do not hesitate to contact the Editorial Office.Thank you for your contribution to Molecular Systems Biology.

Yours sincerely,
Poonam Bheda, PhD Scientific Editor Molecular Systems Biology ------->>> Please note that it is Molecular Systems Biology policy for the transcript of the editorial process (containing referee reports and your response letter) to be published as an online supplement to each paper.If you do NOT want this, you will need to inform the Editorial Office via email immediately.More information is available here: https://www.embopress.org/transparentprocess#Review_Process

EMBO Press Author Checklist USEFUL LINKS FOR COMPLETING THIS FORM
The EMBO Journal -Author Guidelines EMBO Reports -Author Guidelines Molecular Systems Biology -Author Guidelines EMBO Molecular Medicine -Author Guidelines Please note that a copy of this checklist will be published alongside your article.

Abridged guidelines for figures 1. Data
The data shown in figures should satisfy the following conditions: New materials and reagents need to be available; do any restrictions apply?Not Applicable

Antibodies
Information included in the manuscript?
In which section is the information available?
(Reagents and Tools Plants: provide species and strain, ecotype and cultivar where relevant, unique accession number if available, and source (including location for collected wild specimens).

Not Applicable
Microbes: provide species and strain, unique accession number if available, and source.

Human research participants Information included in the manuscript?
In which section is the information available?
(Reagents and Tools If your work benefited from core facilities, was their service mentioned in the acknowledgments section?Not Applicable

Design
Study protocol Information included in the manuscript?
In which section is the information available?
(Reagents and Tools a statement of how many times the experiment shown was independently replicated in the laboratory. -common tests, such as t-test (please specify whether paired vs. unpaired), simple χ2 tests, Wilcoxon and Mann-Whitney tests, can be unambiguously identified by name only, but more complex techniques should be described in the methods section; Please complete ALL of the questions below.Select "Not Applicable" only when the requested information is not relevant for your study.a specification of the experimental system investigated (eg cell line, species name).the assay(s) and method(s) used to carry out the reported observations and measurements.an explicit mention of the biological and chemical entity(ies) that are being measured.
the data were obtained and processed according to the field's best practice and are presented to reflect the results of the experiments in an accurate and unbiased manner.ideally, figure panels should include only measurements that are directly comparable to each other and obtained with the same assay.
an explicit mention of the biological and chemical entity(ies) that are altered/varied/perturbed in a controlled manner.the exact sample size (n) for each experimental group/condition, given as a number, not a range; a description of the sample collection allowing the reader to understand whether the samples represent technical or biological replicates (including how many animals, litters, cultures, etc.).Include a statement about sample size estimate even if no statistical methods were used.

Yes Figure
Were any steps taken to minimize the effects of subjective bias when allocating animals/samples to treatment (e.g.randomization procedure)?If yes, have they been described?

Not Applicable
Include a statement about blinding even if no blinding was done.

Yes
Blinding was not employed as it was deemed not relevant to the experimental design and objective.Describe inclusion/exclusion criteria if samples or animals were excluded from the analysis.Were the criteria pre-established?
If sample or data points were omitted from analysis, report if this was due to attrition or intentional exclusion and provide justification.

Not Applicable
For every figure, are statistical tests justified as appropriate?Do the data meet the assumptions of the tests (e.g., normal distribution)?Describe any methods used to assess it.Is there an estimate of variation within each group of data?Is the variance similar between the groups that are being statistically compared?

Yes
Used non-parametric tests as appropriate

Sample definition and in-laboratory replication
Information included in the manuscript?
In which section is the information available?
(Reagents and Tools

Reporting
Adherence to community standards Information included in the manuscript?
In which section is the information available?
(Reagents and Tools Have primary datasets been deposited according to the journal's guidelines (see 'Data Deposition' section) and the respective accession numbers provided in the Data Availability Section?

Not Applicable
Were human clinical and genomic datasets deposited in a public accesscontrolled repository in accordance to ethical obligations to the patients and to the applicable consent agreement?

Not Applicable
Are computational models that are central and integral to a study available without restrictions in a machine-readable form?Were the relevant accession numbers or links provided?

Materials and Methods. Also Github provided
If publicly available data were reused, provide the respective data citations in the reference list.

Not Applicable
The MDAR framework recommends adoption of discipline-specific guidelines, established and endorsed through community initiatives.Journals have their own policy about requiring specific guidelines and recommendations to complement MDAR.

Figure 2 D
Figure 2 D. The Y-axis is lacking a clear title indicating the represented parameter (survival of E. coli BL21).I added this information to the Y axis as suggested.
of type VI secretion system effector-immunity pairs using structural bioinformatics Dear Dr Levy, 3) Please place individual sections of the manuscript in the following order: Title page -Abstract & Keywords -Introduction -Results -Discussion -Materials & Methods -Data Availability -Acknowledgements -Disclosure and Competing Interests Statement -References -Figure Legends -Tables -Expanded View Figure Legends.-The main and EV figure legends need to be moved to come after the References.4) For the figures and figure legends, please take care of the following: -Please note that information related to n is missing in the legend of Figure EV 2b.-Please note that we require exact p-values to be reported.Currently exact p-values are not provided in Figure EV 4a or its legend.

I
look forward to reading a new revised version of your manuscript as soon as possible.

3)
Please place individual sections of the manuscript in the following order: Title page -Abstract & Keywords -Introduction -Results -Discussion -Materials & Methods -Data Availability -Acknowledgements -Disclosure and Competing Interests Statement -References -Figure Legends -Tables -Expanded View Figure Legends.24th Mar 2024 2nd Authors' Response to Reviewers -The main and EV figure legends need to be moved to come after the References.I placed the sections in the order as instructed, including moving the Figure and EV Figure legends to after the references.4) For the figures and figure legends, please take care of the following: -Please note that information related to n is missing in the legend of Figure EV 2b.I added the relevant information including k and n: "Bars represent mean, error bars represent standard deviation of k = 10 instances of k-fold validation performed on a dataset of n=164 pairs (95 in positive set, 69 in the negative set)" Yes, you can publish the PRF 10) Please provide a point-by-point letter INCLUDING my comments as well as the reviewer's reports and your detailed responses (as Word file).Okay I integrated your comments, as well as our cover letter in response to your comments, and the point by point response.I look forward to reading a new revised version of your manuscript as soon as possible.
plots include clearly labeled error bars for independent experiments and sample sizes.Unless justified, error bars should not be shown for technical if n<5, the individual data points from each experiment should be plotted.Any statistical test employed should be justified.Source Data should be included to report the data underlying figures according to the guidelines set out in the authorship guidelines on Data Each figure caption should contain the following information, for each panel where they are relevant: 10) We replaced Supplementary Information with Expanded View (EV) Figures and Tables that are collapsible/expandable online.A maximum of 5 EV Figures can be typeset.EV Figures should be cited as 'Figure

In which section is the information available?
definitions of statistical methods and measures: (Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section)

In which section is the information available?
Table, Materials and Methods, Figures, Data Availability Section) (Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section)

materials Information included in the manuscript? In which section is the information available?
(Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section)Cell lines: Provide species information, strain.Provide accession number in repository OR supplier name, catalog number, clone number, and/OR RRID.

In which section is the information available?
Provide species, strain, sex, age, genetic modification status.Provide accession number in repository OR supplier name, catalog number, clone number, OR RRID.
(Reagents and ToolsTable, Materials and Methods, Figures, Data Availability Section) Laboratory animals or Model organisms:

In which section is the information available?
Table, Materials and Methods, Figures, Data Availability Section) If collected and within the bounds of privacy constraints report on age, sex and gender or ethnicity for all study participants.(Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section)

Reporting Checklist for Life Science Articles (updated January
This checklist is adapted from Materials Design Analysis Reporting (MDAR) Checklist for Authors.MDAR establishes a minimum set of requirements in transparent reporting in the life sciences (see Statement of Task: 10.31222/osf.io/9sm4x).Please follow the journal's guidelines in preparing your manuscript.For clinical trials, provide the trial registration number OR cite DOI.
If study protocol has been pre-registered, provide DOI in the manuscript.

In which section is the information available?
(Reagents and ToolsTable, Materials and Methods, Figures, Data Availability Section) Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section) (

or biological replicates. Yes Figures Ethics Ethics Information included in the manuscript? In which section is the information available?
Table, Materials and Methods, Figures, Data Availability Section) In the figure legends: state number of times the experiment was replicated in laboratory.Yes Figures In the figure legends: define whether data describe technical (Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section) Studies involving human participants: State details of authority granting ethics approval (IRB or equivalent committee(s), provide reference number for approval.Include a statement confirming that informed consent was obtained from all subjects and that the experiments conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report.State if relevant permits obtained, provide details of authority approving study; if none were required, explain why.
Not ApplicableStudies involving human participants: For publication of patient photos, include a statement confirming that consent to publish was obtained.Not Applicable Studies involving experimental animals: State details of authority granting ethics approval (IRB or equivalent committee(s), provide reference number for approval.Include a statement of compliance with ethical regulations.Not ApplicableStudies involving specimen and field samples:

Use Research of Concern (DURC) Information included in the manuscript? In which section is the information available?
(Reagents and ToolsTable, Materials and Methods, Figures, Data Availability Section) Could your study fall under dual use research restrictions?Please check biosecurity documents and list of select agents and toxins (CDC): https://www.selectagents.gov/sat/list.htmNot Applicable If you used a select agent, is the security level of the lab appropriate and reported in the manuscript?Not Applicable If a study is subject to dual use research of concern regulations, is the name of the

authority granting approval and reference number for
the regulatory approval provided in the manuscript?

and III randomized controlled trials
Table, Materials and Methods, Figures, Data Availability Section) State if relevant guidelines or checklists (e.g., ICMJE, MIBBI, ARRIVE, PRISMA) have been followed or provided.Not Applicable For tumor marker prognostic studies, we recommend that you follow the REMARK reporting guidelines (see link list at top right).See author guidelines, under 'Reporting Guidelines'.Please confirm you have followed these guidelines., please refer to the CONSORT flow diagram (see link list at top right) and submit the CONSORT checklist (see link list at top right) with your submission.See author guidelines, under 'Reporting Guidelines'.Please confirm you have submitted this list.Reagents and Tools Table, Materials and Methods, Figures, Data Availability Section) (